CLASSIFYING VEGETATION USING NASA's EXPERIMENTAL ADVANCED AIRBORNE RESEARCH LIDAR (EAARL) AT ASSATEAGUE ISLAND NATIONAL SEASHORE 1
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Amar Nayegandhi , John C. Brock , C. Wayne Wright
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ETI Professionals, Inc. U.S. Geological Survey Saint Petersburg, FL 33702
[email protected] 2
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U.S. Geological Survey Saint Petersburg, FL 33702
[email protected] NASA Wallops Flight Facility Wallops Island, VA 23337
[email protected] ABSTRACT The NASA Experimental Advanced Airborne Research Lidar (EAARL) acquired airborne lidar data for beach and vegetated communities at Assateague Island, Maryland, in September 2002 and August 2004. The EAARL system is a raster-scanning, temporal-waveform-resolving, green-wavelength lidar designed to map nearshore bathymetry, topography, and vegetative structure simultaneously. The NASA EAARL sensor records the time history of the return waveform for each laser pulse, enabling characterization of canopy structure and “bare earth” under a variety of vegetation types. Each lidar waveform describes the time-resolved amplitude of a reflected laser pulse as a function of the laser pulse time of flight at 1-nanosecond duration. The small footprint (20 cm at nominal flying altitude of 300 m), high pulse repetition frequency (up to 5 KHz), and narrow field of view of the EAARL sensor yield the very high spatial resolution of the system. The EAARL system also includes a 3-band color-infrared (CIR) multispectral camera that is tightly coupled with lidar acquisition. Information from EAARL overflights and accompanying ground-based field measurements is used to evaluate the capability of lidar data to determine the vertical distribution of canopy and sub-canopy across a diverse set of vegetation classes. Composite waveforms (5m diameter) that describe a significant horizontal area were determined from the EAARL small-footprint waveforms. Vegetation metrics such as canopy heights and canopy reflection ratio were derived from the composite waveforms and were applied to differentiate between the formation classes within the physiognomic level of the U.S. National Vegetation Classification System. Results show that vertical canopy information from a waveformresolving lidar system can reliably differentiate among forests, woodlands, and shrublands, which are difficult to discern from digital camera imagery, thereby improving the capability to classify vegetation on this barrier island.
INTRODUCTION Assateague Island National Seashore (ASIS) is a 59.5-km-long coastal barrier island, bordered on the east by the Atlantic Ocean and on the west by the Sinepuxent Bay. The island consists of 19,425 hectares in the states of Maryland and Virginia, encompassing sandy beaches, coastal wetlands, and upland vegetated communities. Barrierisland vegetation communities are strongly influenced by littoral geomorphic processes. The effects of salt spray, winds, and sand movement during frequent storm events define the types of vegetation and wildlife habitats that can survive on a barrier island. Effective resource management of barrier islands requires the creation of accurate and detailed maps of vegetation at periodic intervals. Legislation specific to ASIS directs the National Park Service (NPS) to ensure that natural ecosystem processes proceed unimpaired by human intervention. Attempts to produce accurate topographic beach and vegetation maps of ASIS were initiated in 1995 and are still underway. The first lidar topographic survey over Assateague Island was conducted using NASA's Airborne Topographic Mapper (ATM) in 1995 (Krabill et al., 2000). The primary focus was to demonstrate the application of ASPRS 2005 Annual Conference “Geospatial Goes Global: From Your Neighborhood to the Whole Planet” March 7-11, 2005 Baltimore, Maryland
airborne remote sensing for beach monitoring, providing highly detailed beach morphology in reasonable agreement with available ground-profile surveys. Subsequently, 13 ATM lidar missions have been conducted at ASIS, and the Digital Elevation Models (DEMs) derived from these data have been used to study beach and shoreline change and its effect on the island ecosystem (Sallenger et al., 1999, Brock et al., 2001). The ATM is a “single-return” lidar; the instrument records the range to the first significant object in the path of the laser illumination. Over a vegetated terrain, this first return defines the elevation of the upper layer of the canopy. Most current discrete-return lidar devices measure the range to one to four objects within the canopy by identifying, in the return signal, major peaks that represent laser reflections from discrete objects along the pulse path and within the laser footprint (Wehr & Lohr, 1999). These high-density discrete-return lidars provide opportunities to model above-ground biomass and canopy volume by determining forest attributes such as canopy height (Lim et al., 2003). The structure and shape of measured tree crowns were determined using a high-density lidar data set with distances of 44 to 48 cm between laser hits. Holmgren & Persson (2004) used the structure and shape data to discriminate between individual trees (Scotts pine and Norway spruce). Waveform-recording devices differ from discrete-return devices because they record the time-varying intensity of the returned energy from each laser pulse, providing information about the vertical distribution of surfaces illuminated by the laser pulse (Lefsky et al., 2002). Several studies have shown that large-footprint (typically 10- to 25-m-diameter) lidar data can be used to characterize the total volume and spatial organization of vegetation material within the forest canopy (Blair et al., 1999; Lefsky et al., 1999b; Harding et al., 2001). The ability to characterize the vertical distribution within the canopy can be used to differentiate between several plant communities with similar upper vegetation stratum composition. This paper discusses the ability of a unique smallfootprint waveform-resolving lidar to characterize vegetation structure. The instrument, the NASA Experimental Advanced Airborne Research Lidar (EAARL), uses a green-wavelength laser to map nearshore bathymetry, topography and vegetation structure simultaneously (Wright & Brock, 2002). The goal of this paper is to: 1. derive a composite “large-footprint” waveform from the EAARL small-footprint waveforms to describe the vertical structure of a vegetated canopy; 2. derive vegetation metrics such as canopy height and canopy reflection ratio from the composite waveforms; 3. and use these metrics to differentiate between the formation classes within the physiognomic level of the U.S. National Vegetation Classification System at Assateague Island.
The NASA EAARL Sensor The EAARL sensor suite includes a raster-scanning, temporal waveform-resolving adaptive lidar, a downlooking color (RGB) camera, and a high-resolution color-infrared (CIR) digital camera (Figure 1). The accurate geolocation of each EAARL spot requires precise knowledge of the time of day, the aircraft attitude (pitch, roll, heading), and the precise geographic location in latitude, longitude, and altitude above the WGS-84 ellipsoid. The precision attitude is acquired from an Inertial Measurement Unit (IMU). Attitude information is also available from a Trimble TANS-Vector GPS-based attitude system at 10 Hz. Geolocation is obtained by kinematic GPS measurements of the primary EAARL GPS antenna made relative to a fixed GPS antenna at the departure airport or a nearby location. The design specifications (Table 1) of the EAARL system reveal affinities with both traditional green-laser bathymetric lidars (Guenther, 2001) and common near-infrared lidars used routinely for mapping sub-aerial topography (Fowler, 2001). The EAARL laser transmitter is a Continuum EPO-5000 doubled YAG laser that can produce up to 10,000 short-duration (1.3 nanosecond), low-power (70 µJ), green-wavelength (532 nm) pulses each second. The EAARL transmitter pulse repetition frequency (PRF) is varied along each across-track raster scan in order to produce equal cross-track sample spacing and near uniform density within the EAARL swath. The average PRF of the EAARL system is 3000 Hz with the peak approaching 5000 Hz through the center of the swath (Wright & Brock, 2002). Each reflected pulse is captured simultaneously by four high-speed temporal waveform digitizers connected to four sub-nanosecond photo detectors that vary in brightness sensitivity. Real-time software is used to adapt to each laser return waveform automatically and retain only the relevant portions of the digitized return for recording. The EAARL data system consists of high-speed micro-controllers and a custom-built interface card that attaches to a Linux computer. The data are stored on a set of 46 and 250 Gigabyte hard drives. A typical mission results in 10-50 Gigabytes of lidar and photographic data. The EAARL system incorporates a Duncan Tech MS-4000 high-resolution color infrared (CIR) multispectral camera and an Axis 2120 down-looking RGB digital network camera, both of which capture photographs continuously at a 1-Hz rate. The digital cameras are co-registered to the EAARL optical system. The CIR camera produces 18-cm-resolution pixels at nominal flying altitude of 300 m. ASPRS 2005 Annual Conference “Geospatial Goes Global: From Your Neighborhood to the Whole Planet” March 7-11, 2005 Baltimore, Maryland
Results from EAARL missions in the Tampa Bay region (Brock et al., 2002) and along the Florida Keys reef tract (Brock et al., 2004) show that the system is able to perform cross-environment surveys routinely in a single overflight. Table 1: NASA EAARL specifications Total system weight Maximum power requirement Nominal surveying altitude Nominal surveying speed Raster scan rate Laser sample per raster Swath width at 300 m altitude Sample spacing
Area surveyed per hour (300 m altitude, 50 m/s) Nominal power required Illuminated laser spot diameter on the surface Nominal ranging accuracy
Nominal horizontal positioning accuracy Digitizer temporal resolution
Figure 1: The EAARL sensor suite
Minimum water depth Maximum measurable water depth
250 lbs. 28 VDC at 26 amps 300 m AGL 97 knots (50 m/s) 25 rasters per second 120 240 m Swath center 2×2m Swath edges 2×4m 43 km2 per hour 400 Watts 20 cm Topographic 3 cm Bathymetric TBD 60% canopy cover > 5 m canopy height 10-60% canopy cover > 5 m canopy height 10-100% canopy cover 1-5 m canopy height Herbaceous vegetation, sand, shrubs < 1 m in height
Number of Correctly Field samples classified
% correct
16
14
87.5
6
4
66.67
7
5
71.4
5
5
100
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(a) (b) Figure 6: Classification results from a sample vegetated region at ASIS. (a) RGB image. (b) Resulting classification based on canopy reflection ratio and canopy height derived from 5-m composite EAARL waveforms.
ACKNOWLEDGEMENTS The U.S. Geological Survey Biological Resources Division (BRD) National Resources Preservation Program (NRPP) has funded this investigation. The authors thank Virgil Rabine for his excellent skills as Chief Pilot and Mark Duffy for GPS base-station support during the NASA EAARL surveys; Melanie Harris for assistance in preparation of the figures; and Lance Mosher for assistance in processing the EAARL lidar data. Mike Oconnell, Mark Sturm, and Helen Hamilton from the National Park Service (NPS) are gratefully acknowledged for conducting field measurements in support of this investigation. Any use of trade names is for descriptive purposes only and does not imply endorsement by the U.S. Government.
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